KEOP-2005 집중관측자료를 이용한 관측시스템 실험 연구
Observing System Experiments Using the Intensive Observation Data during KEOP-2005
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초록
The intensive upper-air observation network was organized over southwestern region of the Korean Peninsula during the Korea Enhanced Observing Program in 2005 (KEOP-2005). In order to examine the effect of additional upper-air observation on the numerical weather forecasting, three Observing System Experiments (OSEs) using Korea Local Analysis and Prediction System (KLAPS) and Weather Research and Forecasting (WRF) model with KEOP-2005 data are conducted. Cold start case with KEOP-2005 data presents a remarkable predictability difference with only conventional observation data in the downstream and along the Changma front area. The sensitivity of the predictability tends to decrease under the stable atmosphere. Our results indicates that the effect of intensive observation plays a role in the forecasting of the sensitive area in the numerical model, especially under the unstable atmospheric conditions. When the intensive upper-air observation data (KEOP-2005 data) are included in the OSEs, the predictability of precipitation is partially improved. Especially, when KEOP-2005 data are assimilated at 6-hour interval, the predictability on the heavy rainfall showing higher Critical Success Index (CSI) is highly improved. Therefore it is found that KEOP-2005 data play an important role in improving the position and intensity of the simulated precipitation system.
Abstract
The intensive upper-air observation network was organized over southwestern region of the Korean Peninsula during the Korea Enhanced Observing Program in 2005 (KEOP-2005). In order to examine the effect of additional upper-air observation on the numerical weather forecasting, three Observing System Experiments (OSEs) using Korea Local Analysis and Prediction System (KLAPS) and Weather Research and Forecasting (WRF) model with KEOP-2005 data are conducted. Cold start case with KEOP-2005 data presents a remarkable predictability difference with only conventional observation data in the downstream and along the Changma front area. The sensitivity of the predictability tends to decrease under the stable atmosphere. Our results indicates that the effect of intensive observation plays a role in the forecasting of the sensitive area in the numerical model, especially under the unstable atmospheric conditions. When the intensive upper-air observation data (KEOP-2005 data) are included in the OSEs, the predictability of precipitation is partially improved. Especially, when KEOP-2005 data are assimilated at 6-hour interval, the predictability on the heavy rainfall showing higher Critical Success Index (CSI) is highly improved. Therefore it is found that KEOP-2005 data play an important role in improving the position and intensity of the simulated precipitation system.
참고문헌 (28)
- 한반도 악기상 집중관측 사업(Ⅰ), "기상연구소", 기상연구소, 279~, pp.기상연구소 연구보고서, MR010F08 (2001)
- 한반도 악기상 집중관측 사업(Ⅱ), "기상연구소", 기상연구소, 279~, pp.기상연구소 연구보고서, MR020F08 (2002)
- 한반도 악기상 집중관측 사업(Ⅲ), "기상연구소", 기상연구소, 321~, pp.기상연구소 연구보고서, MR030F07 (2003)
- 한반도 악기상 집중관측 사업(Ⅳ), "기상연구소", 기상연구소, 362~, pp.기상연구소 연구보고서, MR040F01 (2004)
- 김기훈, "한반도 남서지역 집중관측 자료를 활용한 겨울철 강수 사례 분석", 한국기상학회 봄철 학술대회 논문집, pp.292~293 (2006)
- 김용상, "기상연구소의 국지규모 기상 분석 및 예측 시스템(KLAPS)의 실시간 운영", 한국기상학회지, 38(1), pp.1~10 (2002), 한국기상학회
- 박영연, "KEOP-2004 집중관측 자료에 대한 강수예측의 민감도 분석", 대기, 17(4), pp.435~453 (2007), 한국기상학회
- 박옥란, "해남 윈드프로파일러와 오토존데 자료를 이용한 관측시스템 연구", 한국기상학회지, 41(1), pp.57~71 (2005), 한국기상학회
- 백선균, "윈드프로파일러를 이용한 2003년 여름철 악기상 현상 분석", 대기, 13, pp.156~157 (2003)
- 변재영, "WRF 모델에서 모의된 2005년 장마 기간 강수의 동조성 연구", 대기, 17(2), pp.115~123 (2007), 한국기상학회
- 오재호, "장마집중감시(KORMEX)", 한국자료분석학회지, 2, pp.423~439 (2000)
- 원혜영, "윈드프로파일러 관측자료를 이용한 장마철 강수 형태 분류와 관련된 종관장 특성 분석: 2003년-2005년", 대기, 16(3), pp.235~246 (2003)
- Amstrup, B., "Impact of the additional FASTEX radiosonde observations on the High- Resolution Limited-Area Model (HIRLAM) data-assimilation and forecasting system", Quart. J. Roy. Meteor. Soc., 125, pp.3359~3374 (1998)
- Arnold, C. P. Jr., "Observing- Systems Simulation Experiments: Past, present, and future", Bull. Amer. Meteor. Soc., 67, pp.687~695 (1986)
- Atlas, R., "Atmospheric observations and experiments to assess their usefulness", J. Meteor. Soc. Japan, 75, pp.111~130 (1997)
- Chen, F., "Coupling an advanced land surface-hydrology model with the Penn State- NCAR MM5 modeling system. PartⅠ: Model implementation and sensitivity", Mon. Wea. Rev., 129, pp.569~585 (2001)
- Heming, J. T., "The impact of surface and radiosonde observations from two Atlantic ships on a numerical weather prediction model forecast for the storm of 25 January 1990", Meteorol. Mag., 119, pp.249~259 (1990)
- Hirschberg, P. A., "An Observing system experiment with the west coast picket fence", Mon. Wea. Rev., 129, pp.2585~2599 (2001)
- Hong, S.-Y., "Nonlocal boundary layer vertical diffusion in a medium-range forecast model", Mon. Wea. Rev., 124, pp.2322~2339 (1996)
- Song-You Hong, "The WRF Single-Moment 6-Class Microphysics Scheme (WSM6)", 한국기상학회지, 42(2), pp.129~151 (2006), 한국기상학회
- Joly, A., "EXperiment (FASTEX) project", Quart. J. Roy. Meteor. Soc., 125, pp.3131~3163 (1999)
- Kain, J. S., "The Kain-Fritsch convective parameterization: An update", J. Appl. Meteor., 43, pp.170~181 (2004)
- Kallen, E., "The influence of isolated observation on short range numerical weather forecasts", Tellus, 40A, pp.324~336 (1988)
- Langland, R. H., "The North Pacific Experiment (NORPEX-98) : Targeted observations for improved North American weather forecasts", Bull. Amer. Meteor. Soc., 80, pp.1363~1384 (1999)
- Observing system experiment on North Atlantic radiosondes, "Lonnberg, P.", HIRLAM, ~, pp.HIRLAM Tech. Rep., 22. SMHI. S-601 76 Norrkoping (1996)
- Mlawer, E. J., "Radiative transfer for inhomogeneous atmosphere: RRTM, a validated correlated-k model for the longwave", J. Geophys. Res., 102(D14), pp.16663~16682 (1997)
- Unden, P., "Recent observing system experiment at ECMWF", Proceedings of CGC-WMO workshop on the impact of various observing systems on numerical weather prediction, pp.12~27 (1997)
- Wilks, D. S., "Statistical methods in the atmospheric sciences; an introduction", pp.467~ (1995), Academic Press, Inc.